Category: Jessica’s Status Reports

This week, I presented our final presentation and worked on the demo video. Specifically, for the demo video, I helped film and edit the video.

My progress is on-track. Next week, I plan to submit the demo video and work on our final report.

 

This week, I helped to retrain the image classifier on Resnet101, collect latency and accuracy data, synthesize the data, and update our final presentation slides.

My progress is on-track. Next week, I hope to present our final presentation and to continue retraining the image classifier (potentially on a larger image dataset or a Resnet model with more layers) to further improve accuracy.

This week, I helped to find additional garbage image datasets, relabel images from our dataset, and retrain the image classifier. I also wrote short scripts to help with these steps which should speed up the process next week. So far, we have been training on the Jetson Nano, but ideally we would use AWS. I set up an instance on AWS this week, but could not figure out how to retrain the Resnet50 model using our dataset.

My progress is on-track. Our entire project is integrated and we have already added more pictures to our dataset. Next week, I hope to continue updating the image dataset, retraining the image classifier, and testing the overall accuracy. I will also continue to experiment with AWS, but if that does not work, training on the Jetson Nano is sufficient though slightly inconvenient.

This week I integrated the mechanism with the Jetson Nano, integrated the sensor classifiers with the motor control, and started integrating our classifiers together with the motor control. Currently, the sensor classifiers are integrated with the motor control, but I still need to finish up adding the image classifier. I also helped Tate with assembling the mechanism and testing it without the sliding box.

My progress on the image classifier is slightly behind because we were not able to mount the camera and sensor platform to the trash shell until very late in the week, so we were not able to start collecting image data. Thus, the accuracy on our image classifier is lower than expected, but this should be fine for the demo. The image classifier is also not integrated with the motor control yet, but we will still be able to show the image classifier working separately with live camera input for our demo.

Next week I hope to test the mechanism with the sliding box, start retraining the image classifier on real objects, and finish integrating all of classifiers together with the motor control.

 

 

This week, I set up everything on the Jetson Nano to replace the Jetson Xavier. I also hooked up the motor the motor driver/Jetson Nano, set up and ran the image classifier on the Jetson Nano, modified our pre-existing CAD models to for our larger gear size, and began writing the sensor classifiers.

My progress is currently on schedule. At the beginning of the week, the Jetson Xavier became unresponsive, so debugging the Xavier and setting up everything again on the Nano took a lot of time, but I was able to catch up by the end of the week.

Next week, I hope to help integrate all of our components with the Jetson Nano. I also hope to improve the accuracy of the image classifier and integrate it with both the camera and the sensor classifiers.

 

 

This week, I helped to wire all of our inductive/capacitive sensors together and measure their output voltage/current to ensure that wiring that number of sensors in parallel would not damage the Jetson Xavier. I also continued downloading dependencies to the Jetson Xavier so that we could correctly interface with the motor driver, camera, sensors, and neural net model. I was able to hook up the Jetson Nano with the Raspberry Pi camera and a simple LED. Then, with Lauren,  I tested the motor driver and the sensors. We were able to hook up multiple inductive and capacitive sensors to the Jetson Xavier, but could not get the motor driver to drive our stepper motor.

My progress is slightly behind schedule. I underestimated the amount of time it would take to set up the Jetson Xavier and interface all of our sensors/motor with it. Installing PyTorch and all of its dependencies on the Jetson Xavier was also more challenging than I expected. However, after testing the sensors, my team realized that calibrating the sensors should take much less time than expected, so we were able to modify our schedule to account for the extra time spent connecting everything to the Jetson Xavier.

Next week, I hope to get the motor driver working successfully and finish installing the necessary machine learning libraries so that we can test the image classifier. Once that’s done, I can help build the sensor box and mount our sensors to it.

This week, I mainly helped Tate prepare for the Design Review presentation and began working on the design report. I have added more detail to our system diagram and started filling out our BOM in more detail. I also decided to modify our mechanism to follow the design of a previous project of mine so that we can reuse parts and do not need to waste time CADing/3D-printing. We will need to slightly modify the mechanism’s dimensions, gear size, and moving platform to fit our project. From my calculations, a 1.65″ diameter gear with our 600rpm stepper motor should be able to meet our mechanism latency metric. The other modifications have also been accounted for. In addition to working on the mechanism, I met with my team today to begin testing our sensors. So far, all sensors except our load sensor have been tested.

My progress is currently on schedule. Next week, I hope to continue working on the design report. Then, I hope to start attaching the sensors to our platform and start building the image classifier.

This week, I focused on preparing our design presentation. For the slides, I mainly filled out the block diagram and  mechanical solution and implementation sides. With my group, I then met with our professor and the TA to discuss potential improvements to our presentation. After some advice from our TA to add more implementation details, Lauren and I met to finalize sensor placement and Jetson Nano GPIO allocation.

I also spent a lot of time finalizing the mechanism.  After deciding to reduce our target mechanism latency to <1s last week, I began researching different linear motor actuators. The main types of mechanisms I found were screwball, rack and pinion, and belt driven. It seems like all of these mechanisms are suitable for our use case given that we can adjust the mechanism speed based on gear sizes. I was also able to find CAD mechanisms for the rack and pinion and belt driven mechanisms so that we can hopefully laser cut most of our mechanism.

My progress is slightly behind. I focused most of my time on the hardware aspect of our project and on finalizing the slides, so I was not able to research different image classification models. Hopefully, we can use the resnet model that Lauren and I found a couple of weeks ago.

Next week, I hope to hook up our sensors to an Arduino and begin collecting data. Although we have a general idea of which stepper motors and motor drivers we want, we also need to submit the purchasing request.

This week, I mainly researched different sensors so that we could submit our first purchase request by the end of this week. I tried to find sensors with a decent sensing range that fit within our budget, but most sensors have around an 8mm range. From the sensors that I researched, we ended up purchasing an inductive, capacitive, and load sensor. My group also met with our TA to further discuss our mechanism and our requirements. After our discussion, we decided to tighten the requirements to 90% classification accuracy and 1-2 second latency.

Our project is still on-schedule. Next week, I plan to finalize our mechanism, order the mechanism parts, and prepare for our design presentation.

This week, I helped to narrow down the scope of our project and further develop our project. Specifically, I researched  potential sensors that we could use in the case that our classifier was not accurate enough. We ended up choosing an IR and inductive sensor that were mentioned in a garbage segregation research paper that I had found. I also helped to finalize our mechanism and modify our proposal presentation slides due this weekend .

Our project is still on-schedule. During the week, we had to schedule extra meetings with our professor and TA to address some problems with our idea, but we have now resolved all of those issues.

Next week, I plan to start the design process including finalizing budget, making preliminary sketches of the mechanism, and beginning to prepare for our design presentation in two weeks.

 

Some resources for sensors:

https://lillych.in/files/Chin-2019-icra.pdf

https://iopscience.iop.org/article/10.1088/1742-6596/1007/1/012057/pdf